The Trust Layer for AI
Deterministic Controls — 3 minutes to production.
AI agents are autonomous. Trust isn't.
The problem isn't a single vulnerability. It's architectural.
Unclear identity and intent
Agent A calls Agent B. B has no idea what A is allowed to do. Creates holes in probabilistic defenses.
Boundaries multiply
LangChain → MCP → API. Attack surface growing faster than reactive defenses can keep up.
Trust is implicit
Agents can lie, hallucinate, modify logs. Authorization is assumed. Reactive defenses can't keep up.
“You can't bolt trust onto a system designed without it.”
One line of code. Enterprise trust.
Same APIs. Same code. Now with cryptographic security.
# Before from openai import OpenAI client = OpenAI() # After from macaw import SecureOpenAI client = SecureOpenAI() # That's it. Your AI is now trusted.
Works with what you already use
Deterministic Controls for Enterprise AI
No blind spots
Every agent, tool, and LLM gets a signed keypair. Full trace of every operation, invocation, and data access.
- Real-time topology of agents, tools, and connections
- Every node has cryptographic identity — trace anything
- Click any node to see its policies and permissions
How It Works
Tamper-proof, preventative, provable controls for every AI interaction.
App / Agent / Tool
MACAW Trust Layer
Distributed Zero-Trust Mesh
Agent / Tool / LLM
Policy-based Controls
Enforced at Endpoints
Sign
Every operation gets cryptographic identity
Enforce
Policies checked before execution, not after
Attest
Tamper-proof record of who, what, when, why
Prevent, don't detect. Prove, don't promise.
Get started : 3 clicks to production
Connect
Download endpoint + adapter. Connect to trust layer.
Set Policies
Use English, just as you would tell someone.
Operate
Every operation signed, enforced, attested. Trustworthy by default.
Enterprise Ready
Everything you need to ship AI in production.
Identity Bridge
Connect any IDP. Map claims to policies. Switch providers without code changes.
Agentic Traces
End-to-end visibility across request flows, policy resolution, agent lifecycle, and prompt chains.
Tamper-Proof Audit
Hash-chained entries. Cryptographic integrity. Break one link, the chain breaks.
OTEL Integration
Export to your stack — Datadog, Grafana, Splunk. One config.
Policy Inheritance
Hierarchical composition. Permissions only narrow, never expand.
External Attestors
Human-in-the-loop approval. Cryptographically signed sign-off.
Start Now. Scale When Ready.
AI can't wait, neither should you.
Developer (Free)
- 150K events / 30 days
- 3 users
- Cloud (AWS)
- Standard backend & IDP
- BYO LLM
- Console policy management
- Standard enforcement
- Community support
Enterprise
- Configurable limits
- Unlimited users
- Hybrid, multi-cloud
- Configurable backend & IDP
- Per-user LLM controls
- + Git sync, bulk upload
- + Restrictive mode
- Dedicated + SLA
Ship AI your board will approve.
3 minutes to production. No credit card required.